CN110135076A - A kind of holder mechanical structure multiple target integrated optimization method based on ISIGHT associative simulation - Google Patents
A kind of holder mechanical structure multiple target integrated optimization method based on ISIGHT associative simulation Download PDFInfo
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Abstract
The invention discloses a kind of holder mechanical structure multiple target integrated optimization method based on ISIGHT associative simulation, this method is using small-sized multi-rotor unmanned aerial vehicle holder as research object, for multiple target demand of the small-sized multi-rotor unmanned aerial vehicle clouds terrace system to the structure problem low with complicated limit element artificial module optimization efficiency, suitable optimal design parameter is had chosen by sensitivity analysis, utilize response surface model and Establishment of Neural Model approximate model algorithm, in combination with utilize Improving Genetic Algorithm, establish a kind of multiple target integrated optimization algorithm arrangement, realize the high mode multi-objective optimization design of power of lightweight of holder mechanical system.SOLIDWORKS and ANSYS WORKBENCH, which is integrated, the present invention is based on ISIGHT has built union simulation platform, it does not need to establish complicated cradle head structure simulation model, design cycle and cost are also saved in the used time for meeting design requirement, has the characteristics that high efficiency, convenient for Project Realization.
Description
Technical field
The invention belongs to aviation inertially stabilized platform design fields, and in particular to one kind is based on ISIGHT associative simulation
Holder mechanical structure multiple target integrated optimization method, for can also be improved holder machinery knot simultaneously in the requirement for meeting design
The optimization efficiency of structure, the mechanical structure suitable for large, medium and small type unmanned aerial vehicle platform system optimize.
Background technique
Have using multi-rotor unmanned aerial vehicle as the small-sized air remote sensing system of flight carrier and obtains image maneuverability, image
High resolution, it is at low cost the advantages that, become effective supplement of traditional air remote sensing measurement means, be widely used to geographical survey
It draws, electric inspection process, disaster relief, important the army and the people's key areas such as police stability maintenance, and shows huge application potential.For reality
The function of existing multi-rotor unmanned aerial vehicle air remote sensing system needs holder to support and stablizes imaging load, controlled by real-time servo,
The various disturbances in UAV system inside and outside are effectively isolated, guarantee imaging load optic central extract and accurately track target, are effectively prevented
Image quality caused by load shake is imaged to degenerate.Small-sized multi-rotor unmanned aerial vehicle uses holder as a kind of complicated electromechanical servo system
System, it is desirable that have both the electromechanical properties such as lightweight and fast-response.Since the multi-rotor unmanned aerial vehicle as flight carrier has flying ring
The features such as border disturbance is complicated, cruise duration is extremely limited, proposes requirements at the higher level to the overall performance of clouds terrace system.
In multi-rotor unmanned aerial vehicle air remote sensing system, due to as flight carrier multi-rotor unmanned aerial vehicle load capacity difference and
Cruise duration, short feature, needed to mitigate as far as possible the quality of holder.In the precision tracking systems such as holder, with to tracking accuracy
With the raising of rate request, it may cause structural natural frequencies and fall into servo bandwidth, influence system so as to cause system resonance
Function even causes structure to break ring, and mechanical resonant performance is increasingly known as the important limiting factor of system performance.Therefore in holder
In Design of Mechanical Structure, need to optimize to mitigate quality and improve first-order modal frequency as optimization aim.With meter
The development of calculation machine emulation technology, important means of the optimization design as actual engineering design are used widely in many fields.
In Practical Project product design process, optimization design can quickly and effectively search out most from a large amount of different design schemes
Excellent scheme greatly improves the designing quality and efficiency of product, provides a kind of efficiently feasible mode for the design of complex product.
Currently, about system multi-objective optimization design of power scheme to have delivered patent mainly include two classes, the first kind is main
For single emulation platform, such as a kind of patent " optimization design side of the magnetic flow convertor emulated based on genetic algorithm and ANSYS
Method " (CN201410659057.2), including choose magnetic flow convertor driving circuit in resistance, capacitor and driving voltage conduct
Main optimization parameter, the optimization design for carrying out driving circuit is emulated using genetic algorithm combination ANSYS；Second class is mainly based upon
The Design of Structural parameters of a variety of computational theories, such as patent " a kind of mechanical elastic vehicle wheel Design of Structural parameters method "
(CN201810407188.X) propose it is a kind of establish adaptive neural network algorithm, utilize the suitable instruction of Uniform ity Design Method selection
Practice sample, lacks the emulation with system structure model and contact；A kind of patent " space manipulator trajectory planning side of multiple-objection optimization
Method " (CN201810042025.6) is proposed using multi-Objective Chaotic particle swarm optimization algorithm, to the joint in manipulator motion
Trajectory parameters optimize, and do not propose building for design and simulation platform.
To sum up, universal with the development of small-sized unmanned air vehicle technique and application, it is mechanical for small-sized unmanned machine head
The union simulation platform optimization design of system has wide prospect, and the paper practical studies of this respect also compare shortage.This
Patent is from totality, and the ISIGHT union simulation platform that research contents is related to clouds terrace system is built and multi-objective optimization algorithm
Design, guidance and reference will be provided for similar with holder principle structure design.
Summary of the invention
The technical problem to be solved by the present invention is overcoming the shortcomings of existing multiple-objection optimization technology, not perfect, one kind is proposed
Holder mechanical structure and multiple target integrated optimization method based on ISIGHT associative simulation, for meeting the requirement of design simultaneously
The optimization efficiency that can also be improved holder mechanical structure, the mechanical structure suitable for large, medium and small type unmanned aerial vehicle platform system are excellent
Change.
The present invention solve above-mentioned technical problem the technical solution adopted is that
A kind of holder mechanical structure multiple target integrated optimization method based on ISIGHT associative simulation, which is characterized in that packet
Include following steps:
Step (1) builds holder mechanical structure based on ISIGHT Integrated Simulation SOLIDWORKS and ANSYS WORKBENCH
Union simulation platform specifically includes following 4 steps:
Step 11), the three-dimensional part model that holder mechanical structure is established in SOLIDWORKS and assembly body three-dimensional models,
And complete the setting of attribute；
Step 12) imports the SOLIDWORKS model of foundation in the SOLIDWORKS component of ISIGHT, extracts corresponding ruler
Very little parameter or characteristic parameter are realized integrated between two softwares of ISIGHT and SOLIDWORKS；
Step 13), the script file that the simulation flow of ANSYS WORKBENCH is saved as to .wbjn format will execute phase
It answers the autoexec of errorlevel to import in ISIGHT general purpose module, drives the analysis stream of specific ANSYS WORKBENCH
Cheng Zhihang, then using the parameter in the analysis process of ANSYS WORKBENCH output destination file as ISIGHT general purpose module
Output parameter, the analysis process of ANSYS WORKBENCH can be integrated into ISIGHT；
Step 14), under ISIGHT union simulation platform, SOLIDWORKS can make holder mechanical by parametric modeling
The size and feature parameterization of structure three-dimensional model, ANSYS WORKBENCH can carry out finite element modal analysis, warp to holder
Above operation is crossed by the first-order modal frequency parameter in solving result, the modal frequency of parametrization is then stored in format
Simulation optimization calculating process is carried out in the form document of .csv, to complete above step.
Step (2) establishes sample fitting regression model, is then chosen by sensitivity analysis and determines holder mechanical structure three
Design variable of the highly sensitive size as optimization design in frame structure specifically includes following 3 steps:
Step 21), the multiple linear regression model for being fitted system by sample point first；
Two variable linear regression:
Y=c0+c1x1+c2x2
Its derivation is obtained:
Dy=c1dx1+c2dx2
Wherein x1,x2Main effect be respectively c1dx1And c2dx2；
The main effect obtained after input variable normalized is converted percentage contribution by step 22), then sets for correspondence
Count the sensitivity of variable and target variable；
Step 23), according to the design feature and parametric modeling of three frame assembly of holder the case where, determine that initial designs become
Amount carries out sensitivity analysis to these initializaing variables, selects biggish value as optimization design variable.
Step (3), the approximation that quality and first-order modal frequency are established with response surface model and radial basis neural network
Model algorithm designs multiple target integrated optimization algorithm in combination with Improving Genetic Algorithm, solves operation solution procedure and falls into a trap
Excessive, low efficiency deficiency is measured in calculation, specifically includes following 3 steps:
Step 31), the dimensional parameters for selecting sensitivity analysis to determine are as design variable, using Latin hypercube test side
The highly efficient tectonic sieving matrix of method, the second-order response surface quality for establishing three frame assemblies using second-order response surface technology are approximate
Model；
Step 32), the first-order modal frequency that reasonable holder threedimensional model is established by radial base neural net are approximate
Model；Finite element modal analysis method is a kind of nonlinear model of complexity, may determine that second-order response surface not from sample calculation analysis
The accurate approximation of complex model can be provided, therefore the strongest radial base neural net of capability of fitting in three kinds of approximate models is selected to build
The approximate model of the first-order modal frequency of vertical threedimensional model；
Step 33), to a specific optimization problem, suitable optimization algorithm is that optimization is successfully crucial, using changing
Into NSGA-II algorithm carry out multi-objective optimization question solution.
Step (4), platform building and algorithm design it is ready after, complete to platform operation and design result optimization behaviour
Make, and analysis optimization is as a result, specifically include following 4 steps:
The Fruiting coefficient file of quality approximate model and first-order modal frequency approximate model is imported ISIGHT by step 41)
Approximate model component.
Step 42), addition optimization process component set input ginseng in optimization component parameter mapping interface for design variable
Then two parameters of holder quality and first-order modal frequency are set as output parameter by number.
Optimization method is set as NSGA-II in optimization component by step 43), is set according to specific design requirement is designed
The value range for counting parametric variable, is then arranged optimization aim, by the first-order modal frequency and matter of each frame assembly structure of holder
Amount minimizes and is set as optimization aim.
Step 44), running optimizatin process component, obtain optimum results, and analyze result.
The advantages of the present invention over the prior art are that:
(1) it present invention employs the holder mechanical structure multiple target integrated optimization method based on ISIGHT associative simulation, fills
Distribution has waved SOLIDWORKS and ANSYS WORKBENCH in the advantage in respective field, compares when multiple-objection optimization solves
There is preferable accuracy and reliability in single emulation platform and pure theoryization calculating.
When (2) present invention can be good at solving causing to choose design variable due to manual operation by sensitivity analysis
Deficiency further improves efficiency when staff's designing system, optimization analyzing system performance by Computing.
(3) present invention obtains the side R of tilting component, roll component and orientation assembly quality approximate model by error analysis
Error is 0.99, and root-mean-square error is respectively 0.0009,0.0003,0.0005, shows that degree of fitting is fine.Tilting component, cross
The side's the R error for rolling component and orientation assembly approximate model is respectively 0.99,0.98,0.96, root-mean-square error is respectively 0.026,
0.032,0.047 degree of fitting is preferable.This also turns out that second-order response surface can be fitted approximation to the mass property of threedimensional model,
Proof can establish holder 3D solid first-order modal frequency approximate model by radial base neural net.To sum up approximate model
Foundation is rationally reliable.The method for establishing approximate model simultaneously greatly reduces time-consuming when Computing solves, and improves
Optimization efficiency, reduces cost；
(4) present invention uses Revised genetic algorithum, improves global optimizing ability and effect of optimization.
Detailed description of the invention
Fig. 1 is holder mechanical mechanism three-dimensional model diagram of the invention；
Appended drawing reference lists as follows: 1 is azimuth-drive motor, and 2 be damper, and 3 be azimuth axle, and 4 be position-limit mechanism, and 5 be to bow
Motor is faced upward, 6 be pitching shafting, and 7 be pitching frame, and 8 be roll frame, and 9 be roll shafting, and 10 be roll motor, and 11 be orientation
Frame, 12 be camera, and 13 be retaining mechanism, pedestal 14, mounting base 15；
Fig. 2 is flow chart of the method for the present invention；
Fig. 3 is tilting component multiple-objection optimization procedure chart of the invention；
Fig. 4 is roll component multiple-objection optimization procedure chart of the invention；
Fig. 5 is orientation assembly multiple-objection optimization procedure chart of the invention.
Specific embodiment
With reference to the accompanying drawing and specific embodiment further illustrates the present invention.
Fig. 1 is holder mechanical structure three-dimensional model diagram of the invention, comprising: azimuth-drive motor 1, damper 2, and azimuth axle 3,
Position-limit mechanism 4, pitching motor 5, pitching shafting 6, pitching frame 7, roll frame 8, roll shafting 9, roll motor 10, orientation frame
Frame 11；Three frames being distributed from inside to outside are the main structure of holder.Tilting component in three frames includes: pitching motor
5, pitching shafting 6, pitching frame 7；Roll component includes: roll frame 8, roll shafting 9, roll motor 10；Orientation assembly packet
It includes: azimuth-drive motor 1, azimuth axle 3, orientation frame 11.Wherein, azimuth-drive motor 1, pitching motor 5, roll motor 10 are fixed respectively
In azimuth axle 3, pitching shafting 6, roll shafting 9, camera 12 is fixed on pitching frame 7, and pitching frame 7 passes through pitch axis
It is that 6 bearings are hung under roll frame 8, roll frame 8 is hung under orientation frame 11 by the bearing of roll shafting 9, orientation frame 11
It is hung under pedestal 14 by the bearing of azimuth axle 3, pedestal is connected by four linearly coupled dampers 2 with mounting base 15.Simultaneously
In order to guarantee that the movement of three frames 7,8,11 in safely controllable range, guarantees limit mechanically by position-limit mechanism 4.
In order to guarantee safety of the pitching frame 7 when not needing operation, increases retaining mechanism 13, guarantee that it is tight with roll frame 8
It is close to link together.Corresponding to three shaftings of three frames, three frames of holder are provided in the rotation of space three degree of freedom
Function is crucial load position, needs to carry out strength check to it, it is ensured that holder reliably working.Damping in shock isolation system
Device, by absorber external world high-frequency vibratory energy, tentatively filters out the height that holder is subject between pedestal and mounting base
Frequency disturbs.By the organic assembling of each section, holder mechanical system normal reliable is worked.
Fig. 2 is that the present invention is based on the processes of the holder mechanical structure multiple target integrated optimization method of ISIGHT associative simulation
Figure.According to the actual conditions that holder designs, integrating SOLIDWORKS and ANSYS WORKBENCH by ISIGHT, to build joint imitative
True platform.SOLIDWORKS can make the size and feature parameterization of holder threedimensional model, ANSYS by parametric modeling
WORKBENCH can carry out finite element modal analysis to holder, and by the first-order modal frequency parameter in solving result, will join
The modal frequency of numberization is stored in the form document that format is .csv, for other simulation optimization procedure extractions.Holder machinery system
System union simulation platform, which is built, can be divided into the integrated ANSYS WORKBENCH two of the integrated SOLIDWORKS and ISIGHT of ISIGHT
Point.
A kind of holder mechanical structure multiple target integrated optimization method based on ISIGHT associative simulation, the specific method is as follows:
(1) union simulation platform is built based on ISIGHT Integrated Simulation SOLIDWORKS and ANSYS WORKBENCH, solved
It models the deficiency not accurate enough with this conventional method of analysis respectively to system, is specifically divided into following 4 steps.
Step 11) establishes three-dimensional part model and assembly body three-dimensional models in SOLIDWORKS, and completes setting for attribute
It is fixed.
Step 12) imports the SOLIDWORKS model of foundation in the SOLIDWORKS component of ISIGHT, extracts corresponding ruler
Very little parameter or characteristic parameter are realized integrated between two softwares of ISIGHT and SOLIDWORKS；
Step 13), the script file that the simulation flow of ANSYS WORKBENCH is saved as to .wbjn format.Phase will be executed
It answers the autoexec of errorlevel to import in ISIGHT general purpose module, drives the analysis stream of specific ANSYS WORKBENCH
Cheng Zhihang, then using the parameter in the analysis process of ANSYS WORKBENCH output destination file as ISIGHT general purpose module
Output parameter, the analysis process of ANSYS WORKBENCH can be integrated into ISIGHT.
Step 14), under ISIGHT union simulation platform, SOLIDWORKS can make holder three-dimensional by parametric modeling
The size and feature parameterization of model, ANSYS WORKBENCH can carry out finite element modal analysis to holder, by above
By the first-order modal frequency parameter in solving result, it is .csv's that the modal frequency of parametrization, which is then stored in format, for operation
In form document, completes above step and carry out simulation optimization calculating process.
(2) sample fitting regression model is established, the Gao Ling determined in three-frame structure is then chosen by sensitivity analysis
Design variable of the sensitivity size as optimization design is specifically divided into following 3 steps.
Step 21), the multiple linear regression model for being fitted system by sample point first；
By taking two variable linear regression as an example:
Y=c0+c1x1+c2x2
Its derivation is obtained:
Dy=c1dx1+c2dx2
Wherein x1,x2Main effect be respectively c1dx1And c2dx2。
The main effect obtained after input variable normalized is converted percentage contribution by step 22), then sets for correspondence
Count the sensitivity of variable and target variable.
Step 23), according to the design feature and parametric modeling of three frame assembly of holder the case where, determine that initial designs become
Amount carries out sensitivity analysis to these initializaing variables, selects biggish value as optimization design variable.
(3), the approximate model of quality and first-order modal frequency is established with response surface model and radial basis neural network
Algorithm designs multiple target integrated optimization algorithm in combination with Improving Genetic Algorithm, solves calculation amount in operation solution procedure
Excessive, low efficiency deficiency is specifically divided into following 3 steps.
Step 31), the dimensional parameters for selecting sensitivity analysis to determine are as design variable, using Latin hypercube test side
The highly efficient tectonic sieving matrix of method, the second-order response surface model of three frame assemblies is established using second-order response surface technology.
Step 32) establishes reasonable holder 3D solid first-order modal frequency approximation mould by radial base neural net
Type.Finite element modal analysis method is a kind of nonlinear model of complexity, may determine that second-order response surface cannot from sample calculation analysis
The accurate approximation of complex model is provided, therefore the strongest radial base neural net of capability of fitting in three kinds of approximate models is selected to establish
The approximate model of the first-order modal frequency of threedimensional model.
Step 33), to a specific optimization problem, suitable optimization algorithm is that optimization is successfully crucial.Use with
Under improved NSGA-II algorithm carry out the solution of multi-objective optimization question.
(4), after platform building and algorithm design are ready, the operation to platform operation and design result optimization is completed, and
Analysis optimization is as a result, be specifically divided into following 4 steps.
Step 41), the approximate mould that the Fruiting coefficient file of quality approximate model and mode approximate model is imported to ISIGHT
Type component.
Step 42), addition optimization process component set input ginseng in optimization component parameter mapping interface for design variable
Then two parameters of holder quality and first-order modal frequency are set as output parameter by number.
Optimization method is set as NSGA-II in optimization component by step 43), is set according to specific design requirement is designed
The value range for counting parametric variable, is then arranged optimization aim, by the first-order modal frequency and matter of each frame assembly structure of holder
Amount minimizes and is set as optimization aim.
Step 44), running optimizatin process component, obtain optimum results, and analyze result.
The optimization process of three frame assemblies is respectively as shown in Fig. 3,4,5.Fig. 3 is tilting component multiple-objection optimization procedure chart；
Fig. 4 is roll component multiple-objection optimization procedure chart；Fig. 5 is orientation assembly multiple-objection optimization procedure chart.
For the optimum results of three frame assemblies of holder, each optimization point mass and first-order modal frequency respectively is comprehensively compared
Effect of optimization, select an optimization point as final system design point respectively.Following table is the matter of three frame assemblies of optimization front and back
Amount and first-order modal frequency comparison.Find out from optimum results, while the quality of three frame assembly of holder mechanical system reduces, one
Rank modal frequency is improved.Especially for the pitching frame of compact structure, optimization remaining is bigger, and effect of optimization is more
Add obvious.
The optimization of table 1 front and back cradle head structure performance comparison
The content that description in the present invention is not described in detail belongs to the prior art well known to those skilled in the art.
Claims (5)
1. a kind of holder mechanical structure multiple target integrated optimization method based on ISIGHT associative simulation, which is characterized in that including
Following steps:
Step (1) builds holder mechanical structure joint based on ISIGHT Integrated Simulation SOLIDWORKS and ANSYS WORKBENCH
Emulation platform；
Step (2) establishes sample fitting regression model, is then chosen by sensitivity analysis and determines three frame of holder mechanical structure
Design variable of the highly sensitive size as optimization design in structure；
Step (3), the approximate model that quality and first-order modal frequency are established with response surface model and radial basis neural network
Algorithm designs multiple target integrated optimization algorithm in combination with Improving Genetic Algorithm；
Step (4), platform building and algorithm design it is ready after, complete to platform operation and design result optimization operation, and
Analysis optimization result.
2. a kind of holder mechanical structure multiple target integrated optimization side based on ISIGHT associative simulation according to claim 1
Method, which is characterized in that the union simulation platform in step (1) is built including following 4 steps:
Step 11), the three-dimensional part model that holder mechanical structure is established in SOLIDWORKS and assembly body three-dimensional models, and it is complete
At the setting of attribute；
Step 12) imports the SOLIDWORKS model of foundation in the SOLIDWORKS component of ISIGHT, extracts corresponding size ginseng
Several or characteristic parameter is realized integrated between two softwares of ISIGHT and SOLIDWORKS；
Step 13), the script file that the simulation flow of ANSYS WORKBENCH is saved as to .wbjn format will execute corresponding batch
The autoexec of processing order imports in ISIGHT general purpose module, and the analysis process of specific ANSYS WORKBENCH is driven to hold
Row, then using the parameter in the analysis process of ANSYS WORKBENCH output destination file as the defeated of ISIGHT general purpose module
The analysis process of ANSYS WORKBENCH can be integrated into ISIGHT by parameter out；
Step 14), under ISIGHT union simulation platform, SOLIDWORKS keeps holder mechanical structure three-dimensional by parametric modeling
The size and feature parameterization of model carry out finite element modal analysis to holder by ANSYS WORKBENCH, by solving result
In first-order modal frequency parameter, then by the modal frequency of parametrization be stored in format be .csv form document in, it is complete
Simulation optimization calculating process is carried out above step.
3. a kind of holder mechanical structure multiple target integrated optimization side based on ISIGHT associative simulation according to claim 1
Method, which is characterized in that the carry out sensitivity selection optimization design variable in step (2) includes following 3 steps:
Step 21), the multiple linear regression model for being fitted system by sample point first；
Two variable linear regression:
Y=c0+c1x1+c2x2
Its derivation is obtained:
Dy=c1dx1+c2dx2
Wherein x1,x2Main effect be respectively c1dx1And c2dx2；
The main effect obtained after input variable normalized is converted percentage contribution by step 22), then becomes for corresponding design
The sensitivity of amount and target variable；
Step 23), according to the design feature and parametric modeling of three frame assembly of holder the case where, determine initial designs variable,
Sensitivity analysis is carried out to these initializaing variables, selects biggish value as optimization design variable.
4. a kind of holder mechanical structure multiple target integrated optimization side based on ISIGHT associative simulation according to claim 1
Method, which is characterized in that approximate model and improved adaptive GA-IAGA integrated optimization method in step (3) include following 3 steps:
Step 31), the dimensional parameters for selecting sensitivity analysis to determine are as design variable, more using Latin hypercube test method
For efficient tectonic sieving matrix, the second-order response surface quality approximation mould of three frame assemblies is established using second-order response surface technology
Type；
Step 32) establishes holder 3D solid first-order modal frequency approximate model by radial base neural net；
Step 33), the solution that multi-objective optimization question is carried out using improved NSGA-II algorithm.
5. a kind of holder mechanical structure multiple target integrated optimization side based on ISIGHT associative simulation according to claim 1
Method, which is characterized in that carry out multiple-objection optimization result and analyze to include following 4 steps based on ISIGHT in step (4):
The Fruiting coefficient file of quality approximate model and first-order modal frequency approximate model is imported the close of ISIGHT by step 41)
Like model component；
Step 42), addition optimization process component set input parameter in optimization component parameter mapping interface for design variable,
Then two parameters of holder quality and first-order modal frequency are set as output parameter；
Optimization method is set as NSGA-II algorithm in optimization component by step 43), and design ginseng is arranged according to specific design requirement
The value range of number variable, is then arranged optimization aim, most by the first-order modal frequency of each frame assembly structure of holder and quality
Smallization is set as optimization aim；
Step 44), running optimizatin process component, obtain optimum results, and analyze result.
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| CN111581750A (en) * | 2020-05-21 | 2020-08-25 | 西安交通大学 | Multidisciplinary multi-index product structure optimization design method based on ISIGHT software |
| CN112084708A (en) * | 2020-09-04 | 2020-12-15 | 西南交通大学 | AGV system optimization configuration method based on response surface and genetic algorithm |
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| CN113761634A (en) * | 2021-09-18 | 2021-12-07 | 奥意建筑工程设计有限公司 | Building structure design method based on multi-objective optimization |
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| CN111581750A (en) * | 2020-05-21 | 2020-08-25 | 西安交通大学 | Multidisciplinary multi-index product structure optimization design method based on ISIGHT software |
| CN112084708A (en) * | 2020-09-04 | 2020-12-15 | 西南交通大学 | AGV system optimization configuration method based on response surface and genetic algorithm |
| CN112084708B (en) * | 2020-09-04 | 2022-08-19 | 西南交通大学 | AGV system optimization configuration method based on response surface and genetic algorithm |
| CN113255229A (en) * | 2021-06-10 | 2021-08-13 | 大连理工大学 | Fuel assembly multidisciplinary structural design optimization method based on joint simulation |
| WO2022257308A1 (en) * | 2021-06-10 | 2022-12-15 | 大连理工大学 | Joint simulation-based fuel assembly multi-subject structure design optimization method |
| CN113255229B (en) * | 2021-06-10 | 2023-04-11 | 大连理工大学 | Fuel assembly multidisciplinary structural design optimization method based on joint simulation |
| CN113761634A (en) * | 2021-09-18 | 2021-12-07 | 奥意建筑工程设计有限公司 | Building structure design method based on multi-objective optimization |
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